Qanopee, a Web Application for Scientific Data Management
The project involved the development of a web tool for scientific data management, with a focus on data quality and traceability. The mission took place between April 2017 and March 2018, in collaboration with the MISTEA UMR (Joint Research Unit). The development was supervised by the Information Systems Department (DSI) of INRAE (National Research Institute for Agriculture, Food and Environment).
Tasks & Objectives
As a fullstack developer, my role involved creating a web application for managing scientific data, with a focus on data quality and traceability. One of the main objectives was to develop a tool that could handle various types of scientific data while ensuring their quality and traceability.
Success criteria included not only the development of a functional web application but also the implementation of robust data validation and quality control mechanisms. A key objective was to ensure data traceability throughout the entire lifecycle. Finally, it was essential to develop a user-friendly interface that could facilitate data management.
Actions and Development
My first step was to analyze the requirements and design the data model. I then developed a web application using TypeScript and Angular 2, with a focus on data validation and quality control. For data storage, I used PostgreSQL with a custom schema for scientific data. Regular workshops with users facilitated the development process.
Regular exchanges with the project, scientific, and IT teams, as well as with the former development team, facilitated my work. Collaboration with the MISTEA UMR was crucial for developing a common understanding of the data model and establishing a shared vocabulary. Despite the complexity of the project and significant technical challenges, implementing the data validation and quality control mechanisms represented a major challenge but also a learning opportunity.
Key decisions were made collectively during bi-weekly meetings. For the data model, I presented a Proof of Concept (POC) before implementing the complete solution.
Results
The results are multiple: creation of the Qanopee tool, which successfully managed scientific data while ensuring their quality and traceability. The application received positive feedback from users, particularly for its data validation and quality control features. The data model allowed for a better understanding of scientific data management, while the web application provided a valuable tool for data exploration.
I learned to effectively handle scientific data management, to develop robust web applications, and to create user-friendly interfaces. Finally, the experience of working with scientific data strengthened my understanding of the challenges in data management and improved my ability to communicate complex ideas clearly.
Technical Stack
The technologies used include: TypeScript, Angular 2, PostgreSQL, HTML/CSS, and Linux systems. For the web application, I chose to use a combination of TypeScript and Angular 2, while other technological choices were made to align with the project objectives. The project, complex in terms of both data management and web development, required mastery of both technical and domain-specific knowledge. Existing technical challenges also posed a challenge, which I addressed by developing robust solutions and maintaining clear documentation. Finally, learning to effectively use PostgreSQL for scientific data management constituted an important step in improving the data management process.